AIMC Topic: Tomography, X-Ray Computed
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Artificial intelligence for the detection of airway nodules in chest CT scans.
European radiology
Mar 5, 2025
OBJECTIVES: Incidental airway tumors are rare and can easily be overlooked on chest CT, especially at an early stage. Therefore, we developed and assessed a deep learning-based artificial intelligence (AI) system for detecting and localizing airway n...
A unified approach to medical image segmentation by leveraging mixed supervision and self and transfer learning (MIST).
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 5, 2025
Medical image segmentation is important for quantitative disease diagnosis and treatment but relies on accurate pixel-wise labels, which are costly, time-consuming, and require domain expertise. This work introduces MIST (MIxed supervision, Self, and...
Artificial intelligence-based deep learning algorithms for ground-glass opacity nodule detection: A review.
Narra J
Mar 5, 2025
Ground-glass opacities (GGOs) are hazy opacities on chest computed tomography (CT) scans that can indicate various lung diseases, including early COVID-19, pneumonia, and lung cancer. Artificial intelligence (AI) is a promising tool for analyzing med...
Development and validation of automated three-dimensional convolutional neural network model for acute appendicitis diagnosis.
Scientific reports
Mar 5, 2025
Rapid, accurate preoperative imaging diagnostics of appendicitis are critical in surgical decisions of emergency care. This study developed a fully automated diagnostic framework using a 3D convolutional neural network (CNN) to identify appendicitis ...
Morphological alterations of the thymus gland in individuals with schizophrenia.
Molecular psychiatry
Mar 4, 2025
Despite its critical function in the immune system and accumulating evidence of immunological abnormalities in schizophrenia, the thymus has long been overlooked. We aimed to investigate thymic morphological alterations and their corresponding hetero...
Comparing Artificial Intelligence and Traditional Regression Models in Lung Cancer Risk Prediction Using A Systematic Review and Meta-Analysis.
Journal of the American College of Radiology : JACR
Mar 4, 2025
PURPOSE: Accurately identifying individuals who are at high risk of lung cancer is critical to optimize lung cancer screening with low-dose CT (LDCT). We sought to compare the performance of traditional regression models and artificial intelligence (...
Assessments of lung nodules by an artificial intelligence chatbot using longitudinal CT images.
Cell reports. Medicine
Mar 4, 2025
Large language models have shown efficacy across multiple medical tasks. However, their value in the assessment of longitudinal follow-up computed tomography (CT) images of patients with lung nodules is unclear. In this study, we evaluate the ability...
CT Differentiation and Prognostic Modeling in COVID-19 and Influenza A Pneumonia.
Academic radiology
Mar 3, 2025
RATIONALE AND OBJECTIVES: This study aimed to compare CT features of COVID-19 and Influenza A pneumonia, develop a diagnostic differential model, and explore a prognostic model for lesion resolution.
Prediction of Lymph Node Metastasis in Lung Cancer Using Deep Learning of Endobronchial Ultrasound Images With Size on CT and PET-CT Findings.
Respirology (Carlton, Vic.)
Mar 3, 2025
BACKGROUND AND OBJECTIVE: Echo features of lymph nodes (LNs) influence target selection during endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA). This study evaluates deep learning's diagnostic capabilities on EBUS images f...
Feasibility exploration of myocardial blood flow synthesis from a simulated static myocardial computed tomography perfusion via a deep neural network.
Journal of X-ray science and technology
Mar 3, 2025
BACKGROUND: Myocardial blood flow (MBF) provides important diagnostic information for myocardial ischemia. However, dynamic computed tomography perfusion (CTP) needed for MBF involves multiple exposures, leading to high radiation doses.
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